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DeepSeek-V4.1-Flash-1017 vs Qwen2.5 7B Instruct

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 2.1. Qwen2.5 7B Instruct is 1.7x cheaper per token.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 2.1, ranking #15 overall.

On price, Qwen2.5 7B Instruct is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4.1-Flash-1017

  • overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen2.5 7B Instruct

  • cost matters — it's about 1.7x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Qwen2.5 7B Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.0
#15
2.1
#337
Reasoning
48.6
#18
2.3
#330
Coding
39.1
#15
3.0
#239
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.30 / M
Output price
$1.20 / M
$0.30 / M
Context window
1,048,576
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
Qwen2.5 7B Instruct
Math
31.8#67
8.1#272
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 14 for Qwen2.5 7B Instruct

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Qwen2.5 7B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Qwen2.5 7B Instruct costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) costs the same as Qwen2.5 7B Instruct ($0.30/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 4.0x more expensive than Qwen2.5 7B Instruct ($0.30/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than Qwen2.5 7B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Oct 20 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Alibaba Cloud / Qwen Team
Qwen2.5 7B Instruct
Input tokens$0.30
Output tokens$0.30
Best providerTogether
Notice missing or incorrect data?

Model Size

Parameter count comparison

755.6B diff

DeepSeek-V4.1-Flash-1017 has 755.6B more parameters than Qwen2.5 7B Instruct, making it 9929.0% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 7B Instruct
7.6Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
7.6B
Qwen2.5 7B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Qwen2.5 7B Instruct's 131,072 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Qwen2.5 7B Instruct is limited to 8,192 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 7B Instruct
Input131,072 tokens
Output8,192 tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Qwen2.5 7B Instruct does not.

DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Qwen2.5 7B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Qwen2.5 7B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4.1-Flash-1017

MIT

Open weights

Qwen2.5 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Qwen2.5 7B Instruct was released on 2024-09-19.

DeepSeek-V4.1-Flash-1017 is 25 months newer than Qwen2.5 7B Instruct.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

2.1yr newer
Qwen2.5 7B Instruct

Sep 19, 2024

2.1 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. Qwen2.5 7B Instruct is available from Together.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Qwen2.5 7B Instruct

together logo
Together
Input Price:Input: $0.30/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Qwen2.5 7B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Qwen2.5 7B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Qwen2.5 7B Instruct.

Which is better, DeepSeek-V4.1-Flash-1017 or Qwen2.5 7B Instruct?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 2.1. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Qwen2.5 7B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash-1017 compare to Qwen2.5 7B Instruct in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. Qwen2.5 7B Instruct scores GSM8k: 91.6%, MT-Bench: 87.5%, HumanEval: 84.8%, MBPP: 79.2%, MATH: 75.5%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Qwen2.5 7B Instruct?

Both models cost $0.30 per million input tokens.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Qwen2.5 7B Instruct?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Qwen2.5 7B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash-1017 and Qwen2.5 7B Instruct?

Key differences include LLM Stats Score (51.0 vs 2.1), context window (1.0M vs 131K), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Qwen2.5 7B Instruct?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Qwen2.5 7B Instruct is developed by Alibaba Cloud / Qwen Team.

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